Search EdWorkingPapers
K-12 Education
Displaying 1 - 10 of 704
The path to becoming a school principal is characterized by a variety of trajectories that reflect the diverse experiences and backgrounds of aspiring leaders. While ideally the road to the principalship would result in a proportional and representative body of principals, research has shown this is rarely the case. To gain a better understanding of where sorting mechanisms may occur along the principal pipeline, this paper longitudinally analyzes the full, start-to-finish career trajectories of over 1.6 million educators in Texas for 30 years. Using social sequence analysis and discrete-time hazard modeling, we find that (1) emergent principals tend to stay in their first teaching position longer than other educators and most often take a direct pathway towards the principalship; (2) proportionally, more principals emerge from elementary, ELA, Social Studies, or STEM fields, while fewer come from Special Education; (3) holding other features constant, male and Black educators are more likely to become a principal while female and Hispanic educators are less likely; and (4) educators are more likely to first become principals when transitioning to a smaller school with more Black and/or Hispanic students. While the pipeline does result in a balanced principal market in some areas, increasing efforts to encourage a more diverse content area representation as well as representation for Hispanic educators in Texas will be particularly important.
Whole-school reforms have received widespread attention, but a critical limitation of the current literature is the lack of evidence around whether these extensive and costly interventions improve students’ long-term outcomes after they leave reform schools. Leveraging Tennessee’s statewide turnaround reforms, we use difference-in-differences models to estimate the effect of attending a turnaround middle school on student outcomes in high school, including test scores, attendance, chronic absenteeism, disciplinary actions, drop out, and high school graduation. We find little evidence to support improved long-run student outcomes – mostly null effects that are nearly zero in magnitude. Our results contribute to a broad call for educational researchers to examine whether school reforms meaningfully affect student outcomes beyond short-term improvements in test scores.
Criminal activity is seasonal, peaking in the summer and declining through the winter. We provide the first evidence that arrests of children and reported crimes involving children follow a different pattern: peaking during the school year and declining in the summer. We use a regression discontinuity design surrounding school start dates and an excess crime calculation to show that the school environment increases reported crimes involving children by roughly 50% annually. School exacerbates preexisting inequality in criminal interactions, increasing the Black-white and male-female gaps in reported juvenile crime and arrest rates by more than 40%.
Sometimes a treatment, such as receiving a high school diploma, is assigned to students if their scores on two inputs (e.g., math and English test scores) are above established cutoffs. This forms a multidimensional regression discontinuity design (RDD) to analyze the effect of the educational treatment where there are two running variables instead of one. Present methods for estimating such designs either collapse the two running variables into a single running variable, estimate two separate one-dimensional RDDs, or jointly model the entire response surface. The first two approaches may lose valuable information, while the third approach can be very sensitive to model misspecification. We examine an alternative approach, developed in the context of geographic RDDs, which uses Gaussian processes to flexibly model the response surfaces and estimate the impact of treatment along the full range of students that were on the margin of receiving treatment. We demonstrate theoretically, in simulation, and in an applied example, that this approach has several advantages over current approaches, including over another nonparametric surface response method. In particular, using Gaussian process regression in two-dimensional RDDs shows strong coverage and standard error estimation, and allows for easy examination of treatment effect variation for students with different patterns of running variables and outcomes. As these nonparametric approaches are new in education-specific RDDs, we also provide an R package for users to estimate treatment effects using Gaussian process regression.
Mastery learning – the process by which students must demonstrate proficiency with a single topic before moving on – is well recognized as one of the best ways to learn, yet many teachers struggle or remain unsure about how to implement it into a classroom setting. This study leverages two field experiments to test the efficacy of a program designed to encourage greater mastery learning through technology and proactive continuous teacher support. Focusing on elementary and middle school mathematics, teachers receive weekly coaching in how to use Computer Assisted Learning (CAL) for students to follow a customized roadmap of incremental progress. Results indicate significant intent-to-treat effects on math performance of 0.12-0.22 standard deviations. Further analysis shows that these gains are concentrated among students in classrooms with at least an average of 35 minutes of practice per week. Teachers able to achieve high-dosage practice have a high degree of initial buy-in, a clear implementation strategy for when practice occurs, and a willingness to closely monitor progress and follow-up with struggling students.
The use of four-day school weeks (4dsw) in the United States has expanded rapidly over the past two decades. Previous work examines the impact of 4dsw on student outcomes, but little research to date examines the effect on school employees even though schools in some locales have adopted 4dsw to recruit and retain staff. This paper examines the effect of 4dsw adoption in Oregon, a state with widespread 4dsw use, on teacher and other school staff retention by leveraging a staggered roll-out of the schedule using a difference-in-differences design. We find that adopting a four-day week increased turnover among teachers, but that turnover among non-teaching staff was largely unaffected. The findings suggest that policymakers interested in implementing 4dsw for improved school employee retention should exercise caution and be attentive to the full set of incentives offered to staff.
Paraeducators are among the largest categories of public education employees and are increasingly seen as a pool of potential teachers. However, little is known about paraeducator-to-teacher transitions. Using statewide administrative data, we show that while paraeducators may be more racially/ethnically diverse than the teacher workforce, Black and Hispanic paraeducators are less likely than White paraeducators to transition into teaching. We additionally show that teachers with paraeducator experience are similarly effective to teachers without paraeducator experience. Lastly, we use simulations to show that the potential for the paraeducator-to-teacher pipeline to diversify the teaching profession may be limited unless they are highly targeted. Our results have policy design implications for efforts to expand the paraeducator-to-teacher pipeline or to diversify the teacher workforce.
The U.S. has witnessed a resurgence of labor activism, with teachers at the forefront. We examine how teacher strikes affect compensation, working conditions, and productivity with an original dataset of 772 teacher strikes generating 48 million student days idle between 2007 and 2023. Using an event study framework, we find that, on average, strikes increase compensation by 8% and lower pupil-teacher ratios by 0.5 students, driven by new state revenues. We find little evidence of sizable impacts on student achievement up to five years post-strike, though strikes lasting 10 or more days decrease math achievement in the short-term.
JEL: I22, J30, J45, J52.